TECHNICAL TRAINING MANAGER

• Define and d rive the end-to-end technology learning strategy (AI, cloud, data, modern engineering, architecture, platforms) aligned to business, delivery, and client needs.
• Design and package full-stack talent transformation solutions for strategic clients, including proposals, solution decks, roadmaps, and program architectures.

Trainers, methods, and innovation

• Lead and coach trainers, architects, and SMEs across AI and other key technology areas to deliver high-quality, hands-on programs.
• Introduce new ways of working in tech trainings: labs, projects, hackathons, sandboxes, playbooks, and reusable templates across multiple tech stacks.
• Use learning platforms, virtual labs, and analytics to scale and personalize learningacross AI, cloud, data, and engineering.

Candidate profile Experience and skills

• 1 5 - 1 7 years across software engineering / architecture / cloud / data / AI , with 5+ years in technical training, presales, or L&D leadership.
• Proven experience running large-scale, multi-technology learning programs and presenting confidently to senior client stakeholders.
• Strong grounding in modern engineering, cloud platforms, data/analytics, and applied AI, with excellent communication, storytelling, and slide-building skills.

Education

• Bachelor s in Computer Science/Engineering or related; Master s preferred.

Tech domains, AI learning, and governance

• Own competency paths for different personas across AI, cloud, data, engineering, and platforms (developers, architects, SRE/DevOps, PMs, domain experts, leaders).
• Guide design of learning on generative AI/LLMs plus adjacent areas such as cloud-native architectures, data engineering, APIs/microservices, security, and observability.
• Convert internal and client technology use cases into learning content, labs, and capstones that can be showcased in customer conversations.

Collaboration and delivery

• Act as technology counterpart to Program Management and L&D Operations for large internal and client-facing programs.
• Define entry/exit criteria, assessments, and readiness scorecards for multi-technology academies and transformation initiatives.
• Ensure trainers, labs, content, and environments are ready and aligned with program timelines, SOWs, and client commitments.

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